Deep Learning with Python - Optimizing Deep Learning Models

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Deep Learning with Python - Optimizing Deep Learning Models

Torrent Contents Size: 263.5 MB

Deep Learning with Python - Optimizing Deep Learning Models
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01 - Batch normalization.mp4
MP4
5 MB
01 - Batch normalization.srt
SRT
4.9 KB
01 - Common loss functions in deep learning.mp4
MP4
10.6 MB
01 - Common loss functions in deep learning.srt
SRT
7.9 KB
01 - Continuing to optimize deep learning models.mp4
MP4
6.1 MB
01 - Continuing to optimize deep learning models.srt
SRT
5.4 KB
01 - Optimizing deep learning models.mp4
MP4
3.5 MB
01 - Optimizing deep learning models.srt
SRT
1.5 KB
01 - Parameters versus hyperparameters.mp4
MP4
9.7 MB
01 - Parameters versus hyperparameters.srt
SRT
7.4 KB
01 - The bias-variance trade-off.mp4
MP4
5.9 MB
01 - The bias-variance trade-off.srt
SRT
5.7 KB
01 - The importance of optimizing deep learning models.mp4
MP4
6 MB
01 - The importance of optimizing deep learning models.srt
SRT
5.1 KB
02 - Applying batch normalization to a deep learning model.mp4
MP4
8 MB
02 - Applying batch normalization to a deep learning model.srt
SRT
4.4 KB
02 - Batch gradient descent.mp4
MP4
5.6 MB
02 - Batch gradient descent.srt
SRT
5.9 KB
02 - Key hyperparameters in deep learning.mp4
MP4
14.9 MB
02 - Key hyperparameters in deep learning.srt
SRT
12.6 KB
02 - Lasso and ridge regularization.mp4
MP4
7.5 MB
02 - Lasso and ridge regularization.srt
SRT
6.5 KB
02 - What you should know.mp4
MP4
1.2 MB
02 - What you should know.srt
SRT
1.4 KB
03 - Applying L1 regularization to a deep learning model.mp4
MP4
9.8 MB
03 - Applying L1 regularization to a deep learning model.srt
SRT
4.6 KB
03 - Gradient clipping.mp4
MP4
9.4 MB
03 - Gradient clipping.srt
SRT
7.8 KB
03 - Methods for hyperparameter tuning.mp4
MP4
10.3 MB
03 - Methods for hyperparameter tuning.srt
SRT
10.2 KB
03 - Stochastic gradient descent (SGD).mp4
MP4
4.6 MB
03 - Stochastic gradient descent (SGD).srt
SRT
4.8 KB
03 - Using the exercise files.mp4
MP4
2.8 MB
03 - Using the exercise files.srt
SRT
2.1 KB
04 - Applying L2 regularization to a deep learning model.mp4
MP4
9.6 MB
04 - Applying L2 regularization to a deep learning model.srt
SRT
4.9 KB
04 - Applying gradient clipping to a deep learning model.mp4
MP4
9 MB
04 - Applying gradient clipping to a deep learning model.srt
SRT
4.4 KB
04 - Defining a tunable deep learning model in Keras.mp4
MP4
17.9 MB
04 - Defining a tunable deep learning model in Keras.srt
SRT
9.7 KB
04 - Mini-batch gradient descent.mp4
MP4
5.5 MB
04 - Mini-batch gradient descent.srt
SRT
6.1 KB
05 - Adaptive Gradient Algorithm (AdaGrad).mp4
MP4
8.7 MB
05 - Adaptive Gradient Algorithm (AdaGrad).srt
SRT
7.6 KB
05 - Early stopping and checkpointing.mp4
MP4
5.1 MB
05 - Early stopping and checkpointing.srt
SRT
5.6 KB
05 - Elastic Net regularization.mp4
MP4
4.7 MB
05 - Elastic Net regularization.srt
SRT
4 KB
05 - Using KerasTuner for hyperparameter tuning.mp4
MP4
23.5 MB
05 - Using KerasTuner for hyperparameter tuning.srt
SRT
11.5 KB
06 - Dropout regularization.mp4
MP4
4.7 MB
06 - Dropout regularization.srt
SRT
4.5 KB
06 - Learning rate scheduling.mp4
MP4
11.1 MB
06 - Learning rate scheduling.srt
SRT
8.2 KB
06 - Root Mean Square Propagation (RMSProp).mp4
MP4
4.3 MB
06 - Root Mean Square Propagation (RMSProp).srt
SRT
3.8 KB
07 - Adaptive Delta (AdaDelta).mp4
MP4
2.6 MB
07 - Adaptive Delta (AdaDelta).srt
SRT
2.8 KB
07 - Applying dropout regularization to a deep learning model.mp4
MP4
9.9 MB
07 - Applying dropout regularization to a deep learning model.srt
SRT
4.4 KB
07 - Training a deep learning model using callbacks.mp4
MP4
20 MB
07 - Training a deep learning model using callbacks.srt
SRT
10.2 KB
08 - Adaptive Moment Estimation (Adam).mp4
MP4
6.1 MB
08 - Adaptive Moment Estimation (Adam).srt
SRT
5.2 KB
Bonus Resources.txt
TXT
102.4 B
Get Bonus Downloads Here.url
URL
204.8 B

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